A New Approach to Routing Optimization for Cluster-Based Wireless Sensor Networks using Swarm Intelligence

Enormous growth rate of Wireless Sensor Networks (WSN) in the recent decade mark out a high demand for efficient scalable routing and aggregation protocols. WSN primarily involves with recording and maintaining intercommunications between each nodes and thereby relaying integral information from a geographically challenging location. Given the randomness of the topologies in large scale environments, clustering of nodes have been extensively used, which can isolate some nodes in cardinal scenarios leading to the increase in overall system efficiency. Hence this leaves an expansive genus for the implementation of different optimizing algorithms to make the clustering more efficient. Use of Swarm Intelligence like Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) are already proven algorithm in large scale cluster-based WSN in improving the node cluster connectivity with aim of reducing power consumption. In this paper a new approach with the usage of Constricted Particle Swarm Optimization and the Ant Colony Optimization with levy flight is scoped out, to improve the cluster formations as well as enhancing node-clustering connectivity to facilitate better usage of the Clustering.